Assessment of cockpit information and control field using neural networks and methods

Abstract

The paper deals with the methodology of estimating the cockpit information and control field using indicators of oculomotor activity and a probabilistic neural network, which is used to calculate the final estimate of the considered display version. This methodology was tested on the universal prototyping bench basis with the participation of pilots. The using of this methodology contributes to the rapid and qualitative ergonomic assessment of the cockpit information and control field, which in turn increases the efficiency of human-machine interaction and, as a consequence, the safety of air transportation.